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Data, AI, & Machine Learning
Navigating Responsible Implementation of Data Ethics in the Age of AI
Leaders must be armed with the right tools and knowledge to navigate the ethical implications concerning data to avoid biases .
Leaders must be armed with the right tools and knowledge to navigate the ethical implications concerning data to avoid biases .
Even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans.
Lessons from two leading hospital systems show how to overcome the obstacles to automation.
Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.
When individuals trust that a company is using their data responsibly, they are willing to share more data, enabling the company to increase its customer engagement.